In 1997, Reed Hastings envisioned a digital site where, for a fixed price, customers could watch an endless amount of movies. At that time the technical infrastructure didn’t exist and the viewing public, who had just become accustomed to DVDs, were simply not ready. But Hastings had a clear vision of the future, and he managed to start Netflix, albeit with a temporary business model. Using the good old-fashioned postal service, he rented out DVD movies via a subscription model. In 2011, when Hastings first dared to prioritize streaming and offer customers the opportunity to subscribe to only the digital service at a lower price, he was met by public outcry. 800,000 customers left in protest and the stock price dropped 77 percent in four months. In the long run, Hastings would prevail. In April 2017, Netflix reported about 93 million paying customers worldwide. Thanks to its temporary solution – and the courage to move on to the next business model – Netflix managed to successfully challenge both themselves and the market. They were perfectly prepared for the coming streaming explosion with a core of faithful users, large amounts of behavioral data, industry contacts and, perhaps most importantly, an excellent recommendation engine. Netflix created its own future market.

Robert Wolcott, Professor at the Kellogg School of Management, calls the phenomenon “temporary business ideas”: A company deliberately launches a business concept that cannot last – and uses that window of time to build a position and assets in anticipation of market changes.

Uber has clearly stated that their existing business model, based on freelance chauffeurs, is a temporary solution in expectation of self-driving cars. Google has invested in Nest in order to sneak a thermostat into the smart home of the future. PayPal’s founder, Peter Thiel, said in 1999 that in the future we would all be like mini-ATMs with digital wallets in our mobile phones, but at the time he could only launch a temporary payment solution based on credit cards where users could “beam” the program with their Palm Pilots. Today, over 200 million people use PayPal’s significantly more advanced mobile payment systems.

Fast-moving markets are difficult to assess. But by investing in temporary business models, prospective companies can be at the forefront of the next development stage. More start-ups than established giants invest in temporary solutions. It seems that younger companies are more likely to put energy into understanding the user needs and market structure of the future. For those companies in the midst of digital transformation, this can be an important lesson. Mark Zuckerberg annually convenes all of his employees and partners to present a detailed 10-year vision of how the market will evolve and what role Facebook will play in it. Is he always right? Certainly not, but this provides direction and instills the courage necessary to create temporary business models that will lead to the next success.

What is the difference between a temporary business model and ordinary experimentation? It’s about deliberately creating an in-road to an expected market. It demands an understanding of the direction forward to make the right investment – and the flexibility to adapt as reality unfolds.

Many companies are currently stuck in business models that have served them well for many years, but which are not watertight solutions for tomorrow’s market. If the giant step into the digitally transparent ecosystem of the future is too complicated, perhaps a contemporary version of Hasting’s DVD rental is what could save them.

Sara Öhrvall

Published in Dagens Industri, November 2017

A TEMPORARY SOLUTION MIGHT BE BIG BUSINESS TOMORROW February 14th, 2018admin

The ongoing technological and social transformation we are currently experiencing is often called the fourth industrial revolution. While the fourth industrial revolution is coming, we are starting to wonder how it will impact jobs? Will jobs exists in the future? Are there still humans doing to work? Is robot going to take my job? While the questions remain unanswered, many have been looking for answers by drawing comparisons to the previous industrial revolutions. This has given birth to two schools of thought: for the other, the past this is a cause for pessimism while the other is more inclined to optimism – both of them, however, are missing the real lesson from history.

Hostler was a relatively common occupation in 19th century England referring to a man who was employed to look after horses of people staying at an inn. Hostlers and several other occupations depending on the care of horses were, however, extinct in the beginning of next century due to a revolution in transportation: motorization. According to the other school of thought, this is exactly what is about to happen for hundreds of millions of truckers around the world. Just as internal combustion engine replaced horse as main source of power, machine learning algorithms will eliminate humans from behind the wheel. Self-driving vehicles, however, are only the beginning. In the future, there will be fewer and fewer tasks that intelligent machines cannot do better than humans. Eventually, humans will face the same fate as horse a hundred years earlier – swept away from the economy by the emerging technologies.

Humans are not horses, representatives of the other school of thought rightly point out. Instead of diminishing, technology actually increases the importance of human judgement and creativity. Our species is characterized by our endless inventiveness and bottomless desires making sure we will never ever get enough. Hence, the economic transformations of the past are a cause for future optimism, not pessimism. Yes, hostlers as well as livery-stable keepers were displaced by motorization, but in turn, it created millions of new jobs as drivers, mechanics, road builders and so on. Similarly, driver-less vehicles will create new professions such as remote vehicle operators and give rise to trillion-dollar passenger economy. Hence, the rise of the intelligent machines will not yield to mass unemployment – just like during the previous 200 years.

So, which one of the schools is more right? Neither, I would argue. Both of these narratives share the same shortcoming. They focus on what might happen in the long-term and neglect the more pressing issue right under our noses: the reskilling revolution. In 19th century England, hostlers and the entire society were totally unprepared for disruption driven by the emerging industrial technologies which caused severe social unrest and human suffering. It is no coincidence that Communist Manifesto was originally published when the revolutions of 1848 erupted around Europe. Currently, similar structural change of the labor market is already taking place and it has been estimated that globally as many as 375 million workers will have to switch occupational categories entirely by 2030. However, compared to the previous industrial revolutions, our contemporary societies should have better conditions deal with transformation and the challenges related to that – if we choose to focus on the right things.

What are the right things, then? Based on the experiences of the past industrial revolutions: reskilling, upskilling, life-long learning and smooth job transitions. The skills needed in the labor market are changing rapidly and unlike in 19th century England, these changes have been largely forecasted. We already know that competence, education and learning are the most critical means coping with the transformation. Nevertheless, there are only few practical approaches mapping opportunities for life-long learning, reskilling and job transition. Hence, tackling these issues should be a top priority for both governments and corporations. Only by doing so, we can repeat the achievements of the great technological inventions of the past and at the same lessen the human suffering during the transition.

Otto Tähkäpää

The author is a Foresight Specialist at MindMill Network and a social science historian by education.

Whenever I go to choose a movie to watch, I’m always struck by the fact that the highest-ranking ones don’t appeal to me. I have been wondering if there was something wrong with my taste, but then Wired magazine recently revealed that IMDb’s top movie list allows algorithms to process the voting data – and over 70 percent of that data comes from men. The film site Rotten Tomatoes bases its data analysis on other reviews, but that data comes from a similarly large share of men. In other words, the algorithms that define the world’s best films do so according to men’s preferences. Movies that are ranked high by women do not have a chance at replacing The Godfather or The Dark Knight.

In the current and long-awaited debate on gender equality, it is interesting to reflect on what happens to gender roles when artificial intelligence interprets our data and helps us make decisions. New research from Princeton, published in the scientific journal Science, shows that algorithms to a large extent associate words such as “leadership” and “pay” with men, while words like “home” and “family” are more often connected to women.

With machine learning, when computers sort through large amounts of training data and learn by example, they are using long-ingrained stereotypes hidden in our everyday lives. Machines that are learning to understand human language start from the assumption that a word is best defined by its relationship with other words. Thus machines interpret the word “computer” as something that is related to men, and the word “handicraft” as something that is related to women. This statistical approach captures the cultural and social context of words in a way that reference books have never done – and the algorithm brings our human prejudice into the equation.

We are further contaminating these algorithms through our use of digital services. Most people who are given the task to design a shoe make a male boot and the majority of photographs depicting important occupations contain men. According to researchers at the University of Virginia, machines make gender associations with one third of all objects and that ratio is even higher when it comes to verbs. Google’s software translates gender-neutral pronouns from multiple languages to “he” when the text refers to doctors and “she” when it refers to nurses. It is statistically correct that more doctors are men, but not something that should be communicated as a given.

Microsoft has shown that machines trained on prejudiced original data do not only reflect gender discrimination. Their algorithms connect men with the word “programming” to an even greater extent than what the data actually shows.

When AI-based systems take on increasingly complicated tasks, the risks of automated decision-making increase. If a future kitchen robot serves a man a beer but helps a woman with the dishes, it’s certainly rather annoying. But when robots guide men and women to make different decisions concerning their educations, jobs and pension investments, the consequences become considerably more serious.

Ethical questions about what kind of world we want to teach the computers and how we can get our system to work in the desired direction are extremely relevant. Educational material for children often shows an idealized world, with female role models in traditionally male roles – and the opposite. In the same way, we need gender-conscious algorithms and a modern version of an equality ombudsman to ensure that different individuals are treated fairly. Otherwise there is a risk that the algorithm-driven world will have a far greater affect on us than a few bad film recommendations. We cannot allow the AI systems to confine us to outdated gender roles. Equality in the future must be significantly better than it has been in the past.

From a spider-like helmet on my head my alternating happy, sad and stressful thoughts are channeled to a screen on the wall – which is filled by growing graphs in different colors. Sensors in the helmet read EEG signals as indicators of my feelings. I’m testing Emotiv, which is one of the many new technologies that collect biometric data to measure emotional currents. Today, facial recognition software can pinpoint happiness if you smile into the camera. Our faces are one big field of expression that is easy for machines to learn. A heart bursting with feelings of love can be recorded by the heart rate monitor in a smart watch. Sweat secretions when someone is late for work can be captured by sensors that analyze stress levels.

The happiness of nations and customers’ feelings have long been evaluated with the help of surveys. Now there’s a whole host of new methods that, with input from bodily data, can calculate the most likely emotion at any given time. There is even software that analyzes social media activities, not just our word choices and their import, but also context and patterns. In other words, we have some rather adept happiness meters.

By moving from self-reported happiness in surveys to measuring actual feelings in real-time – and by connecting them with world events – research will come closer to real experiences. Harvard has conducted the study “Track Your Happiness” with the help of an app that measures life happiness. The Hedonometer project has charted happiness levels in US cities by analyzing 37 million tweets by 180,000 people. Now even the great technology giants are getting on the bandwagon. Apple recently invested in a company that measures emotional-based brainwaves and Mark Zuckerberg said last week that Facebook is developing software that can read thoughts and feelings in order to turn them into text. For real.

Technology that reveals our feelings can definitely be an invasion of privacy, but advertisers are rejoicing about how this will improve methods of measuring the effects of marketing. Customer service centers will be able to read customers’ moods using voice analysis, security police will get a new layer of information at airports and other sensitive sites, and it could even help people with autism to better interact with others. We are also going to start seeing products based on emotional data. Nikon is experimenting with a sensor camera that can read location, sound and temperature to customize the photo with an appropriate filter, according to the emotional mood.

One of the most interesting application areas for emotional data would be to expand our rigid GDP measurements to include the value of social interactions that have previously not been measurable, such as friendship, family happiness, ethics and a sense of meaning in life. Data shows, for example, that we have the clearest feelings of happiness when we help others. Several nations talk about well-being as an important goal for sustainable community development. Can we calculate how much we actually take pleasure in parks, sporting events or in having a visible police force in the vicinity? A study in Amsterdam showed that a noise increase from the airport made people unhappier than a decrease in their own incomes.

It follows that in the future we will be able to provide informed answers to the question of how we feel. In my case, with the spider on my head, I could only watch the screen. Yes, thanks, the data says I feel totally fine. Hopefully, it will make us more aware of what contexts we most like to thrive in. The American Meteorological Society recently made an emotional map that shows that happiness is maximized at 57 degrees Fahrenheit (14 degrees Celsius). So enjoy spring and autumn – summer is too hot for happy days.

So once again, everyone was sat around the big table in the conference room on the top floor. It took over a quarter of an hour to deal with the issue at hand. And that issue was changing the time of a scheduled board meeting. Ten well-paid individuals had just spent valuable time feverishly flicking through their diaries – an activity that could have taken just a few minutes with the help of a digital service.

How is it still acceptable to cheerfully defend a fine leather diary against a digital calendar and claim that a Mont Blanc pen is the best tool for a to-do list? How is it that notes and documents are still written locally on each personal computer or, even worse, by hand and disappear in old pads and dusty folders?

The question might seem banal, but it is about focusing on activities that add value rather than wasting time on administration or looking for information. Many minutes per day, perhaps even full-time jobs, could be saved if all the meetings were booked via Doodle instead of in never-ending rounds of e-mails. If everyone used Dropbox to make their documents accessible, even to external partners. If everyone installed smart e-mail filters to sort the wheat from the chaff. If Evernote was used to organise notes, Scannable to save business cards directly into a contact list, Pipes to quickly summarise long texts, Instapaper to collect articles worth reading and make them available to colleagues with a thirst for knowledge. Or if Slack was made the company’s social hub for discussing new ideas and obtaining immediate feedback. The digital economy does not allow important information to be held by a single individual, where it cannot be shared, searched or discussed. It is easy both to misinterpret and to lose the scribblings of a traditional pen.

In an industrial context, potential efficiencies and automation of working processes are defined in detail, with little scope for the individual to express preferences for artisanal working methods. In the service sector, within management teams and administrative units, the situation is very different.

It is time to hack the office worker. In addition to saving time, a digitalised workplace can help with a move away from silos, traditional hierarchies and rigid processes that were suited to a different era. A digital toolbox makes it easier to share knowledge and networks, develop new ideas and collect data for complex decision-making. As companies make increasing use of a flexible workforce with a large proportion of freelancers and distance workers, technology is needed to bridge the physical gap and enable joint discussions, exchanges of ideas and feedback.

According to Quora Research, a substantial 77 percent of young employees in tech-based start-ups are open to ways of working that challenge existing norms. The equivalent figure is only 19 percent among employees at more traditional companies.

It is not difficult for either an individual or a company to carry out an analysis of the worst time wasters and distractions, and then source a suite of digital tools that provide a cure for the chaos – all it takes is the will. Then there are all the digital solutions that open up possibilities for a new way of working. To quote Mark Zuckerberg, Facebook’s founder and CEO, conventional businesses use new technology to simplify what they already do, start-ups use the technology to challenge the way everything is done.

Digitalization has emerged as a top priority on executive management’s agenda these days. A study published in the Harvard Business Review reveals that two-thirds of companies in the United States and Europe now place a strong focus on digitalization. At the board level, interest is weaker. Just under one-third indicates that digitalization is a priority issue. Previous studies have shown that one-fifth of the board of directors have some sort of digital background, but the 2016 Amrop study shows that except for tech companies, the figure is just 8 percent. We see a gap between Management ambitions and Board priorities —one that poses problems. According to Russell Reynolds, companies that have succeeded in closing the gap between Board and Management to share a common digital agenda and a unified technology approach, show 9 percent higher growth, 27 percent better profitability and 12 percent greater market value.

Corporate digital transformation becomes a crucial decision for the board when existing revenue streams must be deprioritized to create space for tomorrow’s business deals. Take Microsoft, which now focuses on the cloud computing business to the benefit of its traditional software. Similarly, boards must give priority to growth investments as new sustainable digital revenues appear on the horizon, such as when Netflix abandoned its in-store DVD distribution, going from bricks to clicks for a rapid global expansion of live streamed content.

When the world is digitalized, the board must follow. Most boards are used to discussing the fundamental changes in corporate organization and work approaches, but on the other hand we see little innovation in their own work. Today’s board agendas are surprisingly similar to those of a century ago. According to McKinsey, boards spend up to 70 percent of meeting time looking through the rearview mirror and dissecting compliance, quarterly, and audit reports. Digital transformation promises a higher tempo than infrequent board meetings. When the markets become more volatile and the executive team is struggling to resolve its immediate challenges, it’s all the more important for boards to keep looking out toward the horizon. Strategy meetings can’t take place annually — people need real-time information, ongoing strategy discussions and more frequent evaluations.

Solving these increasingly complex issues requires creative problem-solving and a more diversified set of approaches — even in the board room. As the number of technical issues grows, so does the need for continuous skill development for board directors. More experts instead of generalists will need to step up to the plate. External specialists are becoming increasingly important in preparing for tough decisions.

So, what tools do boards have at their disposal for managing digital transformation? More and more US companies are adding a digital transformation committee to prepare for decision-making, involving deep-dives of technological changes as well as analyses of policies and incentive schemes to make sure they are promoting digital development.On the market, digital platforms are also being launched to simplify an agile approach to board activities. The board of the future needs digital control systems, much like a cockpit with a complete overview of relevant real-time data.

As industry after industry faces the challenges of new market conditions, boards have got to future-proof their companies. Most businesses aren’t structured to deal with the unknown, and the pace of change accelerates, an increased intensity is needed also in the board work. Synergies between the outlook of the board and the capacity of the organization are needed, to empower companies to implement courageous and transformational changes of their business models.

All over the western world, the number of new driving licenses is decreasing. The decline is dramatic the US, the holy country of car driving, According to Federal Highway Administration, 83% of all Americans (between 16-24) had a driving license in 1983. Today it is less then 65%. The same development is true in Germany, Great Britain, Australia and Sweden.

The role of the car in youth culture is passé. It is more important what social media friends think about your lifestyle than what you neighbors say about your car. A number of studies prove that high usage of internet leads to lower usage of cars. Digital natives prefer access to products and services, rather than owning objects. They regard the car as an unnecessary problem, only bringing complexity to daily life.

In 2004, the total number of kilometers driven per person flattened out, to start a declining trend since 2007. The car as a mode of transportation is consequently questioned even before there is a full-blown effect of video conferencing, e-commerce, digitalized banking and hospital services, all replacing physical visits (where you may need your car). In the digital daily life, it seems like freedom will be to use google, facebook or instagram on your journey, not being locked behind a car wheel.

international innovation rankings, the Nordic countries generally score in a top position. Sweden, for example, ranks number one in the EU Innovation Scoreboard and number two in Global Innovation Index as well as the World Bank Innovation Rank.

But if you dig deeper, you will soon find that a lot of the top performing nations, including Sweden, is strong when it comes to input to innovation – but not innovation that is commercialized or launched in any market. If a country spends a lot on R&D and innovation infrastructure, the ranking position improves but the commercial output can still be pretty low. There is also a difference between countries focusing on imitation compared to cutting-edge innovations. Imitation has been the path for developing countries, but lately a feature of European countries as well.

Maybe it is time to focus a bit more on the input-output level, the number start-ups, jobs, new products and services in the market per invested R&D dollar. Top performing countries when measuring input-output levels are Israel, South Korea and the US. What’s common among them is an active national innovation agenda among politicians with strategic focus areas and prioritized market opportunities – and innovation is a defined area of responsibility included in politicians’ job descriptions. Another common denominator is universities with cutting-edge education and research, with distinct target areas and increased competitive strength as a result. Finally, they have built strong clusters around big corporations and the eco-system results in new start-ups building new commercial value. Strong clusters are of special interest as spin-offs from big corporations generally have a stronger growth than other start-ups.

A top position in an international innovation ranking may not be the answer. Innovation input without a market will not lead to international success. Innovation needs to be a top priority for national governments to build innovation and technology strategies, prioritize investments in strategic focus areas, research and clusters – and to make sure to support R&D investments that at the end of the day will be delivered to the market.

1. It’s all about money. A small local company can’t compete against large global brands with 3 times larger marketing budgets. The best 20 % of marketing is 5 times more effective than mediocre efforts. David can beat Goljat, but David needs to be braver.

2. If marketing is not working, it’s the marketing departments or the ad agency ́s fault. Yes, but: if the management team can’t decide what the company brand stands for, and if they aren’t able to follow through, the others are destined to fail, too.

3. It’s all about creating great marketing campaigns. A great campaign will grab attention, woo new customers and deepen the commitment of existing ones. Yes, but only for awhile.

4. The secret to being customer centric is to ask people what they want. And to believe the things they say in surveys and focus groups. Untrue. And why? Most good intentions rarely lead to action.

5. Marketing is about telling why the brand is great. The more convincing the arguments, the harder you sell, the more like they are to buy. This rarely, if ever, works. Life is, unfortunately, more complicated.

6. In the near future, all we need to do is to invest in marketing automation software. It will turn suspects into prospects and prospects into leads. Marketing automation is able to make the email campaigns less annoying, but it won’t help much, when we want to change people’s perceptions or behavior.

7. Content is king and content marketing is the solution. All we need to do is match great content to our brands and people will love us. Many brands look at Red Bull and thinkthey can do the same. They forget that they haven’t helped anybody to jump from space lately. And that the only story they have might be in fact – quite boring. It is not that easy.

What should you do instead?

1. Crystallize your brand into a promise in a way neither employees nor customers can misunderstand. Be exceptional in at least one thing: Über is the most conventient way to get a ride and pay for it.

2. Do tangible things that deliver the brand promise, not just a campaign. Nissan’s promise is ‘innovation that excites’. They developed a smart watch for their Nismo sports car range. The watch connects the telemetrics of the car to the driver’s pulse.

3. Treat people like wild animals. Respect them but observe what they are actually doing instead of asking what they intend to do. Focus on what pisses them off. Jet Blue observed thatpeople hated the fact that they didn’t have a fast enough internet connection during the flight – and developed their own superfast satellite link.

4. It is not about you. When you engage the audience, let it be more about actual development than just pr. Be like Starbucks, who tell the status and proceeding of customers ideas in their Starbucking by Starbuck initiative.

5. Innovative marketing is not necessarily an action hero making a split between two moving trucks – but merely a great service innovation that makes a difference in people ́s daily life.

6. Doing more is the new norm – and a great way to differentiate. Zappos is just another ecommerce venture with effective delivery, but the longest calls to their customer servicecan take up to 6 hours. In the automation era, the best marketeers are the ones with the best customer service .

7. Never underestimate the power of good deeds or values in action. Convergence is not opposite to good will. Brands that stand for something are more likely to stand the test of time.